Overview

Dataset statistics

Number of variables11
Number of observations999
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory86.0 KiB
Average record size in memory88.1 B

Variable types

Numeric11

Alerts

x_4 is highly correlated with yHigh correlation
y is highly correlated with x_4High correlation
x_4 is highly correlated with yHigh correlation
y is highly correlated with x_4High correlation
x_4 is highly correlated with yHigh correlation
y is highly correlated with x_4High correlation
x_1 has unique values Unique
x_2 has unique values Unique
x_3 has unique values Unique
x_4 has unique values Unique
x_5 has unique values Unique
x_6 has unique values Unique
x_7 has unique values Unique
x_8 has unique values Unique
x_9 has unique values Unique
x_10 has unique values Unique

Reproduction

Analysis started2022-05-16 07:50:56.530652
Analysis finished2022-05-16 07:51:09.161494
Duration12.63 seconds
Software versionpandas-profiling v3.2.0
Download configurationconfig.json

Variables

x_1
Real number (ℝ≥0)

UNIQUE

Distinct999
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.4908268595
Minimum0.0001881734934
Maximum0.9995660062
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.9 KiB
2022-05-16T10:51:09.530852image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0.0001881734934
5-th percentile0.04234476623
Q10.2189356901
median0.5048459771
Q30.7384930294
95-th percentile0.9483232349
Maximum0.9995660062
Range0.9993778327
Interquartile range (IQR)0.5195573393

Descriptive statistics

Standard deviation0.2938751385
Coefficient of variation (CV)0.5987348345
Kurtosis-1.23314922
Mean0.4908268595
Median Absolute Deviation (MAD)0.2618995951
Skewness-0.0001171731307
Sum490.3360327
Variance0.08636259704
MonotonicityNot monotonic
2022-05-16T10:51:09.637052image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.96837880881
 
0.1%
0.94830391951
 
0.1%
0.90961310621
 
0.1%
0.062880889981
 
0.1%
0.6717807551
 
0.1%
0.11092815221
 
0.1%
0.7068131111
 
0.1%
0.39976672291
 
0.1%
0.83221936671
 
0.1%
0.35282757091
 
0.1%
Other values (989)989
99.0%
ValueCountFrequency (%)
0.00018817349341
0.1%
0.0002376805061
0.1%
0.00033542374151
0.1%
0.00044957455251
0.1%
0.0022745181341
0.1%
0.0024815881621
0.1%
0.0026650598741
0.1%
0.0031082620841
0.1%
0.0053575879431
0.1%
0.0067901229491
0.1%
ValueCountFrequency (%)
0.99956600621
0.1%
0.99900504041
0.1%
0.99822765981
0.1%
0.995723211
0.1%
0.99468274161
0.1%
0.99270354371
0.1%
0.99167595941
0.1%
0.99164929151
0.1%
0.99133249581
0.1%
0.98998260221
0.1%

x_2
Real number (ℝ≥0)

UNIQUE

Distinct999
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.4993099365
Minimum8.508865722 × 10-5
Maximum0.9999592176
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.9 KiB
2022-05-16T10:51:09.718438image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum8.508865722 × 10-5
5-th percentile0.05429990666
Q10.2620030111
median0.5005389699
Q30.7338527376
95-th percentile0.9502933578
Maximum0.9999592176
Range0.999874129
Interquartile range (IQR)0.4718497265

Descriptive statistics

Standard deviation0.2785678267
Coefficient of variation (CV)0.557905634
Kurtosis-1.099712965
Mean0.4993099365
Median Absolute Deviation (MAD)0.2366037248
Skewness-0.002575696342
Sum498.8106266
Variance0.07760003406
MonotonicityNot monotonic
2022-05-16T10:51:09.799588image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.71681978761
 
0.1%
0.064548000461
 
0.1%
0.58344629641
 
0.1%
0.77061789251
 
0.1%
0.95423663241
 
0.1%
0.20480699981
 
0.1%
0.53975622981
 
0.1%
0.44467694661
 
0.1%
0.051132860831
 
0.1%
0.25780797561
 
0.1%
Other values (989)989
99.0%
ValueCountFrequency (%)
8.508865722 × 10-51
0.1%
0.001920715441
0.1%
0.0045105258471
0.1%
0.0073822664561
0.1%
0.0086158781781
0.1%
0.010806137931
0.1%
0.012448583731
0.1%
0.012849200281
0.1%
0.013116265651
0.1%
0.013187739771
0.1%
ValueCountFrequency (%)
0.99995921761
0.1%
0.99966165191
0.1%
0.99849388191
0.1%
0.99680876431
0.1%
0.99633405031
0.1%
0.99598307141
0.1%
0.99527036911
0.1%
0.99415369891
0.1%
0.99363172571
0.1%
0.99337650491
0.1%

x_3
Real number (ℝ≥0)

UNIQUE

Distinct999
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.496888229
Minimum0.003109625774
Maximum0.9989182351
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.9 KiB
2022-05-16T10:51:09.883789image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0.003109625774
5-th percentile0.04575146399
Q10.2317364716
median0.4845410262
Q30.7651983585
95-th percentile0.9440981801
Maximum0.9989182351
Range0.9958086093
Interquartile range (IQR)0.5334618868

Descriptive statistics

Standard deviation0.2978736103
Coefficient of variation (CV)0.5994780977
Kurtosis-1.315259159
Mean0.496888229
Median Absolute Deviation (MAD)0.268836021
Skewness0.01546682282
Sum496.3913407
Variance0.08872868769
MonotonicityNot monotonic
2022-05-16T10:51:09.972347image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.67884646591
 
0.1%
0.83009506971
 
0.1%
0.19640997981
 
0.1%
0.68232393191
 
0.1%
0.37079646181
 
0.1%
0.42625380451
 
0.1%
0.20238120851
 
0.1%
0.092536124171
 
0.1%
0.10265669811
 
0.1%
0.48044515031
 
0.1%
Other values (989)989
99.0%
ValueCountFrequency (%)
0.0031096257741
0.1%
0.0034441035241
0.1%
0.0064407915341
0.1%
0.0074643937411
0.1%
0.0076234634031
0.1%
0.008073755541
0.1%
0.0080875433051
0.1%
0.0089082489721
0.1%
0.011940227121
0.1%
0.012789701581
0.1%
ValueCountFrequency (%)
0.99891823511
0.1%
0.9981922951
0.1%
0.99415195941
0.1%
0.99362079571
0.1%
0.9922772491
0.1%
0.99205686381
0.1%
0.99117564831
0.1%
0.99051517571
0.1%
0.98911239491
0.1%
0.98840572031
0.1%

x_4
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
UNIQUE

Distinct999
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.5032280121
Minimum0.001223057276
Maximum0.9987846948
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.9 KiB
2022-05-16T10:51:10.100892image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0.001223057276
5-th percentile0.05101582825
Q10.2688959518
median0.5037115691
Q30.7478565234
95-th percentile0.9480387195
Maximum0.9987846948
Range0.9975616375
Interquartile range (IQR)0.4789605716

Descriptive statistics

Standard deviation0.2842376007
Coefficient of variation (CV)0.5648286539
Kurtosis-1.153262938
Mean0.5032280121
Median Absolute Deviation (MAD)0.238542805
Skewness-0.005868875243
Sum502.7247841
Variance0.08079101364
MonotonicityNot monotonic
2022-05-16T10:51:10.186167image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.51004887091
 
0.1%
0.39977311761
 
0.1%
0.38089242861
 
0.1%
0.48289145671
 
0.1%
0.59689968851
 
0.1%
0.80601809591
 
0.1%
0.27312334671
 
0.1%
0.12938343711
 
0.1%
0.25854417261
 
0.1%
0.75949943581
 
0.1%
Other values (989)989
99.0%
ValueCountFrequency (%)
0.0012230572761
0.1%
0.0021389536561
0.1%
0.0036908618641
0.1%
0.0041394089351
0.1%
0.0045108885971
0.1%
0.0059405965731
0.1%
0.0062207926531
0.1%
0.0080111795111
0.1%
0.0081521878021
0.1%
0.0081814650911
0.1%
ValueCountFrequency (%)
0.99878469481
0.1%
0.9987578351
0.1%
0.99804498511
0.1%
0.99773001441
0.1%
0.99767996811
0.1%
0.99722899781
0.1%
0.99695481591
0.1%
0.99462096211
0.1%
0.99440018621
0.1%
0.9931339061
0.1%

x_5
Real number (ℝ≥0)

UNIQUE

Distinct999
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.5090419508
Minimum0.005313863512
Maximum0.9984778729
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.9 KiB
2022-05-16T10:51:10.270617image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0.005313863512
5-th percentile0.05816797046
Q10.2745586436
median0.5092126022
Q30.7426676325
95-th percentile0.9524894411
Maximum0.9984778729
Range0.9931640094
Interquartile range (IQR)0.4681089889

Descriptive statistics

Standard deviation0.2834070174
Coefficient of variation (CV)0.5567458967
Kurtosis-1.135675315
Mean0.5090419508
Median Absolute Deviation (MAD)0.2344735903
Skewness-0.02436773506
Sum508.5329089
Variance0.0803195375
MonotonicityNot monotonic
2022-05-16T10:51:10.353951image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.54529913381
 
0.1%
0.37783467841
 
0.1%
0.34703970491
 
0.1%
0.47843130821
 
0.1%
0.49113025821
 
0.1%
0.89996469281
 
0.1%
0.3817732151
 
0.1%
0.36108484261
 
0.1%
0.43370087471
 
0.1%
0.58046450091
 
0.1%
Other values (989)989
99.0%
ValueCountFrequency (%)
0.0053138635121
0.1%
0.0056494479071
0.1%
0.0064963018521
0.1%
0.0066687064251
0.1%
0.0069511658511
0.1%
0.0080623670951
0.1%
0.0081083478871
0.1%
0.0084107951261
0.1%
0.010088756681
0.1%
0.01187895821
0.1%
ValueCountFrequency (%)
0.99847787291
0.1%
0.99819893131
0.1%
0.99790299291
0.1%
0.99733826381
0.1%
0.99647028261
0.1%
0.99609057511
0.1%
0.99541202471
0.1%
0.99427003321
0.1%
0.99343746371
0.1%
0.99243812431
0.1%

x_6
Real number (ℝ≥0)

UNIQUE

Distinct999
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.5135112564
Minimum0.0005168188363
Maximum0.9990590557
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.9 KiB
2022-05-16T10:51:10.436482image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0.0005168188363
5-th percentile0.04917674628
Q10.2554089812
median0.5274046387
Q30.7671528421
95-th percentile0.9518787304
Maximum0.9990590557
Range0.9985422369
Interquartile range (IQR)0.5117438609

Descriptive statistics

Standard deviation0.2912013869
Coefficient of variation (CV)0.5670788775
Kurtosis-1.213893633
Mean0.5135112564
Median Absolute Deviation (MAD)0.2526072282
Skewness-0.08903805937
Sum512.9977451
Variance0.08479824772
MonotonicityNot monotonic
2022-05-16T10:51:10.518026image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.57369221141
 
0.1%
0.87839514181
 
0.1%
0.20161864811
 
0.1%
0.77138699471
 
0.1%
0.83320071831
 
0.1%
0.19701109131
 
0.1%
0.80215749471
 
0.1%
0.29118749151
 
0.1%
0.74915793211
 
0.1%
0.016407209221
 
0.1%
Other values (989)989
99.0%
ValueCountFrequency (%)
0.00051681883631
0.1%
0.0010390782261
0.1%
0.0013802438041
0.1%
0.0018820473921
0.1%
0.0038679060531
0.1%
0.0045784558171
0.1%
0.0058493411631
0.1%
0.0062315419781
0.1%
0.00630565431
0.1%
0.0071640012321
0.1%
ValueCountFrequency (%)
0.99905905571
0.1%
0.99761565051
0.1%
0.99069583111
0.1%
0.98947229681
0.1%
0.98922312911
0.1%
0.98806292541
0.1%
0.98622147721
0.1%
0.98501919841
0.1%
0.98473254151
0.1%
0.98395258581
0.1%

x_7
Real number (ℝ≥0)

UNIQUE

Distinct999
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.4870195881
Minimum0.0004930354189
Maximum0.999179194
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.9 KiB
2022-05-16T10:51:10.602984image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0.0004930354189
5-th percentile0.03986519955
Q10.2376704538
median0.4745734276
Q30.7390013927
95-th percentile0.9330030491
Maximum0.999179194
Range0.9986861586
Interquartile range (IQR)0.5013309389

Descriptive statistics

Standard deviation0.28853689
Coefficient of variation (CV)0.5924543839
Kurtosis-1.200191796
Mean0.4870195881
Median Absolute Deviation (MAD)0.2510147719
Skewness0.05128721269
Sum486.5325685
Variance0.08325353689
MonotonicityNot monotonic
2022-05-16T10:51:10.690393image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.81749124031
 
0.1%
0.10801241151
 
0.1%
0.75658797121
 
0.1%
0.36683586191
 
0.1%
0.46229199411
 
0.1%
0.77575380151
 
0.1%
0.1486540661
 
0.1%
0.24404619221
 
0.1%
0.84553812331
 
0.1%
0.36246803541
 
0.1%
Other values (989)989
99.0%
ValueCountFrequency (%)
0.00049303541891
0.1%
0.0014372125731
0.1%
0.0021687550471
0.1%
0.0022751737851
0.1%
0.0036626441871
0.1%
0.0051782934461
0.1%
0.0051944518931
0.1%
0.0054922809361
0.1%
0.0062931734141
0.1%
0.0067844509611
0.1%
ValueCountFrequency (%)
0.9991791941
0.1%
0.99791088331
0.1%
0.99689040821
0.1%
0.99686666971
0.1%
0.99535173921
0.1%
0.99408103991
0.1%
0.99296431311
0.1%
0.99239844551
0.1%
0.99206752381
0.1%
0.99156689341
0.1%

x_8
Real number (ℝ≥0)

UNIQUE

Distinct999
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.4989466279
Minimum0.0004075991455
Maximum0.9986462623
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.9 KiB
2022-05-16T10:51:10.774919image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0.0004075991455
5-th percentile0.04964895954
Q10.2560673617
median0.5018658189
Q30.737044692
95-th percentile0.9451366704
Maximum0.9986462623
Range0.9982386632
Interquartile range (IQR)0.4809773304

Descriptive statistics

Standard deviation0.2860873305
Coefficient of variation (CV)0.5733826316
Kurtosis-1.201680741
Mean0.4989466279
Median Absolute Deviation (MAD)0.2406459968
Skewness0.008081751893
Sum498.4476812
Variance0.08184596069
MonotonicityNot monotonic
2022-05-16T10:51:10.864333image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.20663621421
 
0.1%
0.75833854381
 
0.1%
0.6485888091
 
0.1%
0.55614282981
 
0.1%
0.44310867021
 
0.1%
0.18646395391
 
0.1%
0.10720316791
 
0.1%
0.5738301071
 
0.1%
0.044935826441
 
0.1%
0.006921989611
 
0.1%
Other values (989)989
99.0%
ValueCountFrequency (%)
0.00040759914551
0.1%
0.0045668333771
0.1%
0.0048197936271
0.1%
0.00501645241
0.1%
0.0052490970121
0.1%
0.006921989611
0.1%
0.0071736779061
0.1%
0.0072984509171
0.1%
0.0073296059851
0.1%
0.010255461791
0.1%
ValueCountFrequency (%)
0.99864626231
0.1%
0.99844628251
0.1%
0.99778709751
0.1%
0.99740617281
0.1%
0.99630194551
0.1%
0.99433335851
0.1%
0.99370873981
0.1%
0.99265730291
0.1%
0.99125769431
0.1%
0.99052470341
0.1%

x_9
Real number (ℝ≥0)

UNIQUE

Distinct999
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.5051851284
Minimum0.007883363403
Maximum0.9988844888
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.9 KiB
2022-05-16T10:51:10.959350image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0.007883363403
5-th percentile0.06057471244
Q10.2621554557
median0.518658031
Q30.7482194676
95-th percentile0.9436818145
Maximum0.9988844888
Range0.9910011254
Interquartile range (IQR)0.4860640119

Descriptive statistics

Standard deviation0.2829511131
Coefficient of variation (CV)0.5600939086
Kurtosis-1.189992985
Mean0.5051851284
Median Absolute Deviation (MAD)0.2438255055
Skewness-0.06801291502
Sum504.6799433
Variance0.08006133242
MonotonicityNot monotonic
2022-05-16T10:51:11.044803image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.8801112271
 
0.1%
0.61697295381
 
0.1%
0.56611506991
 
0.1%
0.45995168391
 
0.1%
0.69529496371
 
0.1%
0.28915176281
 
0.1%
0.72796101241
 
0.1%
0.78635903541
 
0.1%
0.59989839541
 
0.1%
0.75517198961
 
0.1%
Other values (989)989
99.0%
ValueCountFrequency (%)
0.0078833634031
0.1%
0.0084863752131
0.1%
0.0094436474611
0.1%
0.0095534462021
0.1%
0.011772678471
0.1%
0.012025218221
0.1%
0.01285286621
0.1%
0.01322246041
0.1%
0.01766269911
0.1%
0.018250003691
0.1%
ValueCountFrequency (%)
0.99888448881
0.1%
0.99736498411
0.1%
0.99711727561
0.1%
0.99520332761
0.1%
0.99426557361
0.1%
0.99074788281
0.1%
0.98764582351
0.1%
0.98688894491
0.1%
0.98570834051
0.1%
0.9852352381
0.1%

x_10
Real number (ℝ≥0)

UNIQUE

Distinct999
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.4991376114
Minimum0.0001695572864
Maximum0.9988191046
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.9 KiB
2022-05-16T10:51:11.128567image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0.0001695572864
5-th percentile0.05317098475
Q10.2495816054
median0.5095781707
Q30.7423927027
95-th percentile0.9408351386
Maximum0.9988191046
Range0.9986495473
Interquartile range (IQR)0.4928110973

Descriptive statistics

Standard deviation0.2842145647
Coefficient of variation (CV)0.569411237
Kurtosis-1.188904605
Mean0.4991376114
Median Absolute Deviation (MAD)0.2444973388
Skewness0.003290464751
Sum498.6384738
Variance0.0807779188
MonotonicityNot monotonic
2022-05-16T10:51:11.210183image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.57418742521
 
0.1%
0.99566626941
 
0.1%
0.89138154031
 
0.1%
0.41706735081
 
0.1%
0.33670055821
 
0.1%
0.62712393891
 
0.1%
0.38541004951
 
0.1%
0.043236818631
 
0.1%
0.75603172881
 
0.1%
0.68672911591
 
0.1%
Other values (989)989
99.0%
ValueCountFrequency (%)
0.00016955728641
0.1%
0.0021838168611
0.1%
0.0030505326581
0.1%
0.0034604242541
0.1%
0.0050365654751
0.1%
0.0050545190461
0.1%
0.0073212927671
0.1%
0.007510928671
0.1%
0.01488275571
0.1%
0.015248626471
0.1%
ValueCountFrequency (%)
0.99881910461
0.1%
0.99835961641
0.1%
0.99793156911
0.1%
0.99603315331
0.1%
0.99571042951
0.1%
0.99566626941
0.1%
0.99515446251
0.1%
0.99452710151
0.1%
0.99091652641
0.1%
0.99068765061
0.1%

y
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct27
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15.01401401
Minimum3
Maximum29
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.9 KiB
2022-05-16T10:51:11.279649image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile7
Q112
median15
Q318
95-th percentile23
Maximum29
Range26
Interquartile range (IQR)6

Descriptive statistics

Standard deviation4.773612737
Coefficient of variation (CV)0.3179438045
Kurtosis-0.3636394757
Mean15.01401401
Median Absolute Deviation (MAD)3
Skewness-0.006369707158
Sum14999
Variance22.78737856
MonotonicityNot monotonic
2022-05-16T10:51:11.348403image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
1689
 
8.9%
1488
 
8.8%
1784
 
8.4%
1570
 
7.0%
1870
 
7.0%
1365
 
6.5%
1262
 
6.2%
1955
 
5.5%
1153
 
5.3%
953
 
5.3%
Other values (17)310
31.0%
ValueCountFrequency (%)
33
 
0.3%
46
 
0.6%
514
 
1.4%
616
 
1.6%
719
 
1.9%
834
3.4%
953
5.3%
1041
4.1%
1153
5.3%
1262
6.2%
ValueCountFrequency (%)
291
 
0.1%
281
 
0.1%
273
 
0.3%
265
 
0.5%
2513
 
1.3%
2419
1.9%
2312
 
1.2%
2234
3.4%
2144
4.4%
2045
4.5%

Interactions

2022-05-16T10:51:08.039219image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-05-16T10:50:57.728933image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-05-16T10:50:59.143905image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-05-16T10:51:00.449966image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-05-16T10:51:01.369189image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-05-16T10:51:02.287946image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-05-16T10:51:03.238547image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-05-16T10:51:04.393003image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-05-16T10:51:05.254002image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-05-16T10:51:06.104590image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-05-16T10:51:07.150422image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-05-16T10:51:08.115413image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-05-16T10:50:57.904741image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-05-16T10:50:59.246329image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-05-16T10:51:00.535247image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-05-16T10:51:01.455753image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-05-16T10:51:02.364119image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-05-16T10:51:03.313981image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-05-16T10:51:04.467710image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-05-16T10:51:05.329595image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-05-16T10:51:06.179975image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-05-16T10:51:07.239542image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-05-16T10:51:08.192765image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-05-16T10:50:58.010762image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-05-16T10:50:59.720771image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-05-16T10:51:00.629375image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-05-16T10:51:01.540737image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-05-16T10:51:02.439671image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-05-16T10:51:03.386182image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-05-16T10:51:04.539932image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-05-16T10:51:05.406373image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-05-16T10:51:06.308093image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-05-16T10:51:07.313658image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-05-16T10:51:08.271044image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-05-16T10:50:58.124071image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-05-16T10:50:59.799082image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-05-16T10:51:00.723244image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-05-16T10:51:01.626697image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-05-16T10:51:02.517532image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-05-16T10:51:03.462977image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-05-16T10:51:04.615139image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-05-16T10:51:05.486092image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-05-16T10:51:06.417738image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-05-16T10:51:07.391706image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-05-16T10:51:08.348504image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-05-16T10:50:58.237000image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-05-16T10:50:59.872940image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-05-16T10:51:00.814712image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-05-16T10:51:01.717130image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-05-16T10:51:02.591671image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-05-16T10:51:03.543820image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-05-16T10:51:04.697231image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-05-16T10:51:05.566142image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-05-16T10:51:06.521373image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-05-16T10:51:07.468320image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-05-16T10:51:08.431099image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-05-16T10:50:58.338136image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-05-16T10:50:59.947470image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-05-16T10:51:00.892684image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-05-16T10:51:01.792972image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-05-16T10:51:02.728183image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-05-16T10:51:03.621129image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-05-16T10:51:04.776395image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-05-16T10:51:05.638514image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-05-16T10:51:06.606186image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-05-16T10:51:07.544082image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-05-16T10:51:08.511394image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-05-16T10:50:58.438930image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-05-16T10:51:00.023577image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-05-16T10:51:00.977720image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-05-16T10:51:01.880385image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-05-16T10:51:02.823851image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-05-16T10:51:03.719868image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-05-16T10:51:04.852941image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-05-16T10:51:05.718100image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-05-16T10:51:06.693754image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-05-16T10:51:07.617619image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-05-16T10:51:08.587839image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-05-16T10:50:58.555224image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-05-16T10:51:00.106080image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-05-16T10:51:01.053160image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-05-16T10:51:01.973500image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-05-16T10:51:02.924053image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-05-16T10:51:03.801537image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-05-16T10:51:04.927438image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-05-16T10:51:05.799566image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-05-16T10:51:06.796942image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-05-16T10:51:07.693592image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-05-16T10:51:08.666907image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-05-16T10:50:58.724032image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-05-16T10:51:00.190916image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-05-16T10:51:01.126950image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-05-16T10:51:02.053321image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-05-16T10:51:03.010361image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-05-16T10:51:04.159109image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-05-16T10:51:05.012907image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-05-16T10:51:05.877275image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-05-16T10:51:06.890885image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-05-16T10:51:07.781743image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-05-16T10:51:08.742657image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-05-16T10:50:58.843734image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-05-16T10:51:00.285576image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-05-16T10:51:01.211255image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-05-16T10:51:02.128516image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-05-16T10:51:03.091650image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-05-16T10:51:04.238314image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-05-16T10:51:05.094628image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-05-16T10:51:05.955301image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-05-16T10:51:06.972194image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-05-16T10:51:07.877148image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-05-16T10:51:08.822598image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-05-16T10:50:58.968603image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-05-16T10:51:00.368454image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-05-16T10:51:01.289944image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-05-16T10:51:02.208397image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-05-16T10:51:03.165783image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-05-16T10:51:04.319449image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-05-16T10:51:05.172946image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-05-16T10:51:06.033058image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-05-16T10:51:07.065272image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-05-16T10:51:07.960041image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Correlations

2022-05-16T10:51:11.421663image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2022-05-16T10:51:11.518841image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2022-05-16T10:51:11.611371image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2022-05-16T10:51:11.700354image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Missing values

2022-05-16T10:51:08.966635image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
A simple visualization of nullity by column.
2022-05-16T10:51:09.099934image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

First rows

x_1x_2x_3x_4x_5x_6x_7x_8x_9x_10y
00.9683790.7168200.6788460.5100490.5452990.5736920.8174910.2066360.8801110.57418717
10.4682630.4056030.3203250.4680840.1009950.9744070.3000620.6083560.0500820.76201112
20.7768200.1037400.3737480.7977820.9068100.5990690.6266800.9247050.6327680.51266316
30.4078860.4153570.1015430.9351600.4441240.1936070.6568370.5999290.8685820.40540620
40.5387970.0886210.8861190.7818480.4016230.2076520.9463100.7694530.8272920.93718315
50.2068880.9485970.5588840.8717030.4659460.2764750.9899650.7045210.2746290.63253717
60.1871040.9589260.3337850.5531030.3212720.0932460.9920680.6838780.8265430.33998514
70.7799700.7332820.6403200.9884890.5031980.2833500.4120050.6553020.0251550.12086623
80.1939440.8109330.4449940.3305720.5182160.8451870.5258410.7133560.6661830.85687311
90.4342310.7719140.4658470.3711570.8953350.6193490.5976940.7937470.6106310.36371817

Last rows

x_1x_2x_3x_4x_5x_6x_7x_8x_9x_10y
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9980.1812830.9661390.5026680.9858030.2853970.9639760.2832930.8795720.1395730.52307617